Commentary

In this shared blog, David Weisberger says a recent WSJ article is wrong and that traders do need to purchase faster and more comprehensive market data to avoid being fined for violating "Best Execution" obligations.

Algorithms Out of Control?

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Algorithms Out of Control?

Progress always has its downside. Algorithms, when used properly, indisputably reduce transaction costs. These mathematical marvels can lead to better executions. However, flawed algorithms - in a nightmare example of math made too simple - can also be read by trading sharpies. They can read the patterns of some algorithms and front run. "There's a lot of fear that reverse-engineering and pennying problems are causing people using algorithms to incur greater costs than they normally would," says Ben Sylvester, senior trader at money manager David L. Babson & Co. "You have to be cautious about how you use algorithms."

However, the algorithms of recent times are not an accident. They are a

Progress always has its downside.

Algorithms, when used properly, indisputably reduce transaction costs. These mathematical marvels can lead to better executions.

However, flawed algorithms - in a nightmare example of math made too simple - can also be read by trading sharpies. They can read the patterns of some algorithms and front run. "There's a lot of fear that reverse-engineering and pennying problems are causing people using algorithms to incur greater costs than they normally would," says Ben Sylvester, senior trader at money manager David L. Babson & Co. "You have to be cautious about how you use algorithms."

However, the algorithms of recent times are not an accident. They are a response to an environment changed by decimalization and other market structure reforms. These changes fueled algorithmic trading as well as the popularity of ECN and crossing networks. They also promoted the development of direct market access and smart order routing. The reduction in average order size and the decrease in quoted liquidity made algorithmic trading a vital weapon.

A study last year found that 60 percent of buyside firms use algorithmic trading tools to execute orders. Usage is relatively small based on share volume, but it is growing. Traders say they use low-cost algorithmic tools for various reasons: primarily in liquid stocks and to manage workflow and focus on more difficult orders.

But what exactly is algorithmic trading? It covers automated trading in which large orders are broken up and sent into the marketplace according to predetermined quantitative rules. These rules could be based on a number of historical volume patterns, the current day's price and volume activity, as well as other trading signals.

Algorithms are designed to match execution benchmarks. Most traders are familiar with VWAP and TWAP engines. These try to achieve a stock's volume weighted average price, or time weighted average price. Other algorithms aim to match the previous night's close or an implementation shortfall-type benchmark. For example, this could be the portfolio manager's decision price, or the arrival price. This is the price of the stock when the trader receives the order.

Some of the largest providers of algorithmic tools are Credit Suisse First Boston, Goldman Sachs, Bank of America, ITG Inc. and Instinet. Business is good. Algorithmic trading on the buyside may see its share of total order flow rise from five percent in 2004 to 13 percent in 2006, according to the Tabb Group. In comparison, ECN usage over the same period is likely to increase at a slower pace, from 16 percent to 20 percent.